Export application details

Exporting in PICMI allows users to extract application data into a customisable CSV file. This feature enables businesses to work with application data in other tools, like Google Sheets, MacOS Numbers, or Excel. This flexibility ensures your exported data meets the specific requirements of your business or system integration.

What is export?

The export function lets you dynamically extract data from applications, fully customising what is included. You can select:

• Personal answers: Personal/profile responses to any questions in the application workflow
• Summary details: Job-related information
• Contract substitutions: Job or organisational details used in contracts
• Worker information: Profile information about the worker

Key concepts

Columns

Columns represent the data fields in your export. You can add, remove, reorder, or rename columns to suit your needs.

Value & format

Values refer to the data within columns, which can be transformed or masked:

• Transformers: Pre-made settings that adjust the data format
• Masks: Custom rules applied to the data to meet specific needs

Note: there is a default date format that can be changed which is an example of a mask

View

A view is a saved configuration of columns, values, and formats. You can save views to reuse them or create new ones for different purposes.

Specific features

1. Data extraction: Export in CSV format
2. Download or copy: Save as a file or copy to the clipboard for use in other applications
3. Customisable fields: Add, remove, reorder, or rename columns
4. Ad hoc views: Quickly configure exports as needed
5. Repeatable views: Save your setup for future use
6. Data transformation: Apply formatting or masks to fit specific requirements

note

Ready-to-use reports for specific systems are found under Reports (which are CSV integrations)

Working with columns

• Add a column: Include a new field in the export.
• Remove a column: Exclude a field from the export.
• Find specific column by name: Enter a part name to limit the number of fields shown.
• Show columns of type: Choose a column by type (e.g., Summary, Worker, Personal, Contract).
• Add all columns: Include all available fields based on the currently shown columns.
• Remove all columns: Exclude all fields based on the currently shown columns.
• Reorder a column: Change the order in which fields appear.
• Rename a column: Change the name of a field in the export to match your needs.

Working with values

• Change value format: Apply a pre-defined format to the data.
• Add a mask: Customise how data is displayed by applying a mask.
• Set default date format (mask): Customise how all dates are displayed by applying a mask.

Managing views

• Save a view: Store your configuration for future use.
• Choose an existing view: Select a saved configuration.
• Delete a view: Remove a saved configuration you no longer need.

Set default date format

Set as default date format for all dates

Set as default date format allows you to specify a single format that is automatically applied to all date fields in the export. This ensures consistency across the exported data and eliminates the need to individually format each date field. This feature is especially useful when working with large datasets where multiple date fields are present, saving time and ensuring consistent output.

How it works:

1. Default application: Once a default date format is set, every date in the export will automatically use this format unless a specific mask is applied to override it.
2. Global consistency: This ensures all date fields are aligned with a preferred format, making the data easier to read and compatible with downstream systems.

note

Dates will be transformed to local time of the browser ( see conversion of UTC to local time)

Date options

Below is a table illustrating how different date format masks that are applied to the example date 1982-05-25T00:00:00.000Z:

Example date	Format mask option	Explanation
25/05/1982	dd/MM/yyyy	Day with leading zero / Month with leading zero / Full year
25/May/1982	dd/LLL/yyyy	Day with leading zero / Abbreviated month name / Full year
25-05-1982	dd-MM-yyyy	Day with leading zero - Month with leading zero - Full year
25-May-1982	dd-LLL-yyyy	Day with leading zero - Abbreviated month name - Full year
1982/May/25	yyyy/LLL/dd	Full year / Abbreviated month name / Day with leading zero
1982/05/25	yyyy/MM/dd	Full year / Month with leading zero / Day with leading zero
1982-May-25	yyyy-LLL-dd	Full year - Abbreviated month name - Day with leading zero
1982-05-25	yyyy-MM-dd	Full year - Month with leading zero - Day with leading zero
250582	ddMM/yy	Day with leading zero and month without separator / Two-digit year
2582	dM/yy	Day and month without leading zeros / Two-digit year
25051982	ddMM/yyyy	Day with leading zero and month without separator / Full year
251982	dM/yyyy	Day and month without leading zeros / Full year

Formatting transformers

You can apply various formatting types to your data:

Format type	Description
Unformatted (raw)
Number	Formats numbers according to standard conventions
Date	Converts dates into different readable formats
Rich text	Displays text with formatting applied
Bank account	Formats data to match New Zealand bank account standards
Tax number	Formats data to match New Zealand tax number standards
Signature	Formats a signature field if applicable
List value	Extracts the final value from a list (eg, //enum/answer/yes gives yes)
External identifier	Displays the code value and generator type

Understanding masks

Masks in PICMI allow you to transform data by applying custom rules or templates. They provide a way to reformat values to meet specific requirements, ensuring the exported data is tailored for your business or downstream systems.

A mask modifies the raw data into a new format without changing the original value. Here are three examples to demonstrate how masks work:

Date mask

A date mask changes how dates are displayed. For instance, consider a raw date 1982-05-25T00:00:00.000Z. Applying the mask dd/MM/yyyy would reformat the date to:

• Raw value: 1982-05-25T00:00:00.000Z
• Mask: dd/MM/yyyy
• Transformed value: 25/05/1982

This is useful for aligning dates with regional preferences or specific formatting standards required by external systems.

Template mask

This mask combines multiple pieces of data into a structured format. For example, an External Identifier is actually a series of values with the following structure:

{
  value: "A23X5",
  generator: "Five Alphanumeric",
  createdAt: "2024-11-19T12:34:56.000Z",
}

Using the mask ${value} (${generator}), the output would be:

• Raw value: { value: "A23X5", generator: "Five Alphanumeric", createdAt: "2024-11-19T12:34:56.000Z" }
• Mask: ${value} (${generator})
• Transformed value: A23X5 (Five Alphanumeric)

This method allows for combining fields into a readable, concise output suitable for reporting or integration. Note: there is no conditional logic in the templates.